Overview

Dataset statistics

Number of variables20
Number of observations10874
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory160.0 B

Variable types

NUM14
CAT5
BOOL1

Reproduction

Analysis started2021-11-24 10:05:04.156364
Analysis finished2021-11-24 10:05:23.879777
Duration19.72 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

Avg_Open_To_Buy is highly correlated with Credit_LimitHigh correlation
Credit_Limit is highly correlated with Avg_Open_To_BuyHigh correlation
Dependent_count has 920 (8.5%) zeros Zeros
Contacts_Count_12_mon has 277 (2.5%) zeros Zeros
Total_Revolving_Bal has 3875 (35.6%) zeros Zeros
Avg_Utilization_Ratio has 3872 (35.6%) zeros Zeros

Variables

Customer_Age
Real number (ℝ≥0)

Distinct count44
Unique (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.22484826190914
Minimum26
Maximum73
Zeros0
Zeros (%)0.0%
Memory size85.0 KiB
2021-11-24T15:35:23.930839image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile34
Q141
median46
Q351
95-th percentile58
Maximum73
Range47
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.373765181
Coefficient of variation (CV)0.1595195108
Kurtosis-0.09047834281
Mean46.22484826
Median Absolute Deviation (MAD)5
Skewness-0.03106652988
Sum502649
Variance54.37241295
2021-11-24T15:35:23.986646image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
466165.7%
 
445995.5%
 
485925.4%
 
475775.3%
 
495595.1%
 
455575.1%
 
435405.0%
 
425214.8%
 
505014.6%
 
414854.5%
 
Other values (34)532749.0%
 
ValueCountFrequency (%) 
26600.6%
 
27220.2%
 
28240.2%
 
29390.4%
 
30710.7%
 
ValueCountFrequency (%) 
731< 0.1%
 
682< 0.1%
 
673< 0.1%
 
662< 0.1%
 
65630.6%
 

Gender
Categorical

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
F
6079
M
4795
ValueCountFrequency (%) 
F607955.9%
 
M479544.1%
 
2021-11-24T15:35:24.055414image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Dependent_count
Real number (ℝ≥0)

ZEROS

Distinct count6
Unique (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.226871436453927
Minimum0
Maximum5
Zeros920
Zeros (%)8.5%
Memory size85.0 KiB
2021-11-24T15:35:24.112224image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.20642796
Coefficient of variation (CV)0.5417591427
Kurtosis-0.4983526609
Mean2.226871436
Median Absolute Deviation (MAD)1
Skewness0.02289801855
Sum24215
Variance1.455468423
2021-11-24T15:35:24.169034image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2332330.6%
 
3299227.5%
 
1208119.1%
 
4127811.8%
 
09208.5%
 
52802.6%
 
ValueCountFrequency (%) 
09208.5%
 
1208119.1%
 
2332330.6%
 
3299227.5%
 
4127811.8%
 
ValueCountFrequency (%) 
52802.6%
 
4127811.8%
 
3299227.5%
 
2332330.6%
 
1208119.1%
 

Education_Level
Categorical

Distinct count6
Unique (%)0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Graduate
4458
High School
2244
Doctorate
1417
Uneducated
1384
College
909
ValueCountFrequency (%) 
Graduate445841.0%
 
High School224420.6%
 
Doctorate141713.0%
 
Uneducated138412.7%
 
College9098.4%
 
Post-Graduate4624.2%
 
2021-11-24T15:35:24.240798image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length9.13279382
Min length7

Marital_Status
Categorical

Distinct count3
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Married
6053
Single
4208
Divorced
 
613
ValueCountFrequency (%) 
Married605355.7%
 
Single420838.7%
 
Divorced6135.6%
 
2021-11-24T15:35:24.315550image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.669394887
Min length6

Income_Category
Categorical

Distinct count5
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Less than $40K
4599
$80K - $120K
2291
$40K - $60K
1880
$60K - $80K
1365
$120K +
 
739
ValueCountFrequency (%) 
Less than $40K459942.3%
 
$80K - $120K229121.1%
 
$40K - $60K188017.3%
 
$60K - $80K136512.6%
 
$120K +7396.8%
 
2021-11-24T15:35:24.393288image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.20765128
Min length7

Card_Category
Categorical

Distinct count4
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Blue
10223
Silver
 
540
Gold
 
101
Platinum
 
10
ValueCountFrequency (%) 
Blue1022394.0%
 
Silver5405.0%
 
Gold1010.9%
 
Platinum100.1%
 
2021-11-24T15:35:24.470060image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.102997977
Min length4

Months_on_book
Real number (ℝ≥0)

Distinct count44
Unique (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.803935994114404
Minimum13
Maximum56
Zeros0
Zeros (%)0.0%
Memory size85.0 KiB
2021-11-24T15:35:24.533818image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile23
Q132
median36
Q340
95-th percentile48
Maximum56
Range43
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.366607013
Coefficient of variation (CV)0.2057485248
Kurtosis0.6094624981
Mean35.80393599
Median Absolute Deviation (MAD)4
Skewness-0.1255156753
Sum389332
Variance54.26689888
2021-11-24T15:35:24.765833image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
36223520.6%
 
355244.8%
 
344904.5%
 
374634.3%
 
384494.1%
 
334233.9%
 
394233.9%
 
323933.6%
 
403863.5%
 
313813.5%
 
Other values (34)470743.3%
 
ValueCountFrequency (%) 
13490.5%
 
14180.2%
 
15310.3%
 
16230.2%
 
17320.3%
 
ValueCountFrequency (%) 
56670.6%
 
55310.3%
 
54340.3%
 
53500.5%
 
52460.4%
 

Total_Relationship_Count
Real number (ℝ≥0)

Distinct count6
Unique (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4221077800257493
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size85.0 KiB
2021-11-24T15:35:24.823553image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.505394368
Coefficient of variation (CV)0.4399026755
Kurtosis-0.9491254649
Mean3.42210778
Median Absolute Deviation (MAD)1
Skewness0.1281667224
Sum37212
Variance2.266212204
2021-11-24T15:35:24.879436image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3274625.3%
 
2202318.6%
 
4199018.3%
 
5168715.5%
 
6122111.2%
 
1120711.1%
 
ValueCountFrequency (%) 
1120711.1%
 
2202318.6%
 
3274625.3%
 
4199018.3%
 
5168715.5%
 
ValueCountFrequency (%) 
6122111.2%
 
5168715.5%
 
4199018.3%
 
3274625.3%
 
2202318.6%
 

Months_Inactive_12_mon
Real number (ℝ≥0)

Distinct count7
Unique (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3682177671510023
Minimum0
Maximum6
Zeros30
Zeros (%)0.3%
Memory size85.0 KiB
2021-11-24T15:35:24.938241image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9086712506
Coefficient of variation (CV)0.3836941278
Kurtosis1.348401594
Mean2.368217767
Median Absolute Deviation (MAD)1
Skewness0.5509799014
Sum25752
Variance0.8256834416
2021-11-24T15:35:25.001142image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2425039.1%
 
3418138.4%
 
1175516.1%
 
44133.8%
 
51681.5%
 
6770.7%
 
0300.3%
 
ValueCountFrequency (%) 
0300.3%
 
1175516.1%
 
2425039.1%
 
3418138.4%
 
44133.8%
 
ValueCountFrequency (%) 
6770.7%
 
51681.5%
 
44133.8%
 
3418138.4%
 
2425039.1%
 

Contacts_Count_12_mon
Real number (ℝ≥0)

ZEROS

Distinct count7
Unique (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.522254919992643
Minimum0
Maximum6
Zeros277
Zeros (%)2.5%
Memory size85.0 KiB
2021-11-24T15:35:25.063930image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.028031397
Coefficient of variation (CV)0.4075842566
Kurtosis0.2600013447
Mean2.52225492
Median Absolute Deviation (MAD)1
Skewness0.0262617261
Sum27427
Variance1.056848552
2021-11-24T15:35:25.126359image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3405037.2%
 
2364833.5%
 
4132312.2%
 
1130812.0%
 
02772.5%
 
52272.1%
 
6410.4%
 
ValueCountFrequency (%) 
02772.5%
 
1130812.0%
 
2364833.5%
 
3405037.2%
 
4132312.2%
 
ValueCountFrequency (%) 
6410.4%
 
52272.1%
 
4132312.2%
 
3405037.2%
 
2364833.5%
 

Credit_Limit
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count8288
Unique (%)76.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8546.014396974913
Minimum1438.3
Maximum34516.0
Zeros0
Zeros (%)0.0%
Memory size85.0 KiB
2021-11-24T15:35:25.188751image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1438.3
5-th percentile1438.3
Q12413.25
median4402
Q310819.56822
95-th percentile34516
Maximum34516
Range33077.7
Interquartile range (IQR)8406.31822

Descriptive statistics

Standard deviation9203.534695
Coefficient of variation (CV)1.076938824
Kurtosis1.825459053
Mean8546.014397
Median Absolute Deviation (MAD)2623.327158
Skewness1.683041215
Sum92929360.55
Variance84705050.88
2021-11-24T15:35:25.247546image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1438.36175.7%
 
345165935.5%
 
9959120.1%
 
15987100.1%
 
2398180.1%
 
222270.1%
 
200170.1%
 
249070.1%
 
242360.1%
 
622460.1%
 
Other values (8278)960188.3%
 
ValueCountFrequency (%) 
1438.36175.7%
 
1438.3342771< 0.1%
 
1438.3343811< 0.1%
 
1438.5301681< 0.1%
 
1438.5862091< 0.1%
 
ValueCountFrequency (%) 
345165935.5%
 
344961< 0.1%
 
34360.97581< 0.1%
 
34283.009371< 0.1%
 
341981< 0.1%
 

Total_Revolving_Bal
Real number (ℝ≥0)

ZEROS

Distinct count2211
Unique (%)20.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean953.8397093985653
Minimum0
Maximum2517
Zeros3875
Zeros (%)35.6%
Memory size85.0 KiB
2021-11-24T15:35:25.309985image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median917.5
Q31696
95-th percentile2517
Maximum2517
Range2517
Interquartile range (IQR)1696

Descriptive statistics

Standard deviation891.0682687
Coefficient of variation (CV)0.9341907868
Kurtosis-1.334852901
Mean953.8397094
Median Absolute Deviation (MAD)917.5
Skewness0.3038857608
Sum10372053
Variance794002.6594
2021-11-24T15:35:25.366719image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0387535.6%
 
25176165.7%
 
1650100.1%
 
166490.1%
 
86890.1%
 
182990.1%
 
85990.1%
 
154490.1%
 
221680.1%
 
149180.1%
 
Other values (2201)631258.0%
 
ValueCountFrequency (%) 
0387535.6%
 
12< 0.1%
 
31< 0.1%
 
41< 0.1%
 
61< 0.1%
 
ValueCountFrequency (%) 
25176165.7%
 
25151< 0.1%
 
251470.1%
 
25124< 0.1%
 
25113< 0.1%
 

Avg_Open_To_Buy
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count8903
Unique (%)81.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7592.090239423786
Minimum3.0
Maximum34516.0
Zeros0
Zeros (%)0.0%
Memory size85.0 KiB
2021-11-24T15:35:25.427584image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile455.5155101
Q11438.3
median3515
Q39759.964647
95-th percentile32243.35
Maximum34516
Range34513
Interquartile range (IQR)8321.664647

Descriptive statistics

Standard deviation9224.752281
Coefficient of variation (CV)1.215047765
Kurtosis1.807575191
Mean7592.090239
Median Absolute Deviation (MAD)2613.35
Skewness1.676472785
Sum82556389.26
Variance85096054.64
2021-11-24T15:35:25.487315image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1438.34504.1%
 
345161511.4%
 
31999440.4%
 
74060.1%
 
95360.1%
 
11295< 0.1%
 
5195< 0.1%
 
9835< 0.1%
 
7015< 0.1%
 
4635< 0.1%
 
Other values (8893)1019293.7%
 
ValueCountFrequency (%) 
31< 0.1%
 
101< 0.1%
 
10.719988571< 0.1%
 
10.873618791< 0.1%
 
12.091000711< 0.1%
 
ValueCountFrequency (%) 
345161511.4%
 
34504.56811< 0.1%
 
34502.114521< 0.1%
 
34494.649291< 0.1%
 
34494.035721< 0.1%
 

Total_Amt_Chng_Q4_Q1
Real number (ℝ≥0)

Distinct count5395
Unique (%)49.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.734359804631299
Minimum0.0
Maximum3.397
Zeros3
Zeros (%)< 0.1%
Memory size85.0 KiB
2021-11-24T15:35:25.548180image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4301134112
Q10.6050190724
median0.721
Q30.853
95-th percentile1.041545085
Maximum3.397
Range3.397
Interquartile range (IQR)0.2479809276

Descriptive statistics

Standard deviation0.2066949838
Coefficient of variation (CV)0.2814628231
Kurtosis6.444132701
Mean0.7343598046
Median Absolute Deviation (MAD)0.1237696319
Skewness1.041128455
Sum7985.428516
Variance0.04272281631
2021-11-24T15:35:25.609946image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.791270.2%
 
0.838240.2%
 
0.722230.2%
 
0.718230.2%
 
0.744230.2%
 
0.631230.2%
 
0.715220.2%
 
0.681220.2%
 
0.743220.2%
 
0.742220.2%
 
Other values (5385)1064397.9%
 
ValueCountFrequency (%) 
03< 0.1%
 
0.0097761421861< 0.1%
 
0.011< 0.1%
 
0.053715104091< 0.1%
 
0.0612< 0.1%
 
ValueCountFrequency (%) 
3.3971< 0.1%
 
2.5941< 0.1%
 
2.3681< 0.1%
 
2.2751< 0.1%
 
2.1211< 0.1%
 

Total_Trans_Amt
Real number (ℝ≥0)

Distinct count5104
Unique (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3871.287658635277
Minimum569
Maximum18484
Zeros0
Zeros (%)0.0%
Memory size85.0 KiB
2021-11-24T15:35:25.671771image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum569
5-th percentile1131
Q12015
median2668
Q34586
95-th percentile9325.7
Maximum18484
Range17915
Interquartile range (IQR)2571

Descriptive statistics

Standard deviation3051.611876
Coefficient of variation (CV)0.7882679213
Kurtosis4.8227172
Mean3871.287659
Median Absolute Deviation (MAD)1133.5
Skewness2.135184252
Sum42096382
Variance9312335.039
2021-11-24T15:35:25.734557image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2447130.1%
 
2345120.1%
 
2126120.1%
 
2269120.1%
 
1935110.1%
 
2281110.1%
 
1687100.1%
 
2418100.1%
 
2136100.1%
 
2388100.1%
 
Other values (5094)1076399.0%
 
ValueCountFrequency (%) 
5691< 0.1%
 
5851< 0.1%
 
5941< 0.1%
 
5962< 0.1%
 
6131< 0.1%
 
ValueCountFrequency (%) 
184841< 0.1%
 
177441< 0.1%
 
176341< 0.1%
 
174371< 0.1%
 
170931< 0.1%
 

Total_Trans_Ct
Real number (ℝ≥0)

Distinct count124
Unique (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.667279749862054
Minimum10
Maximum139
Zeros0
Zeros (%)0.0%
Memory size85.0 KiB
2021-11-24T15:35:25.796376image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile26
Q140
median51
Q373
95-th percentile95
Maximum139
Range129
Interquartile range (IQR)33

Descriptive statistics

Standard deviation22.50941987
Coefficient of variation (CV)0.397220759
Kurtosis-0.06220861498
Mean56.66727975
Median Absolute Deviation (MAD)15
Skewness0.5980179399
Sum616200
Variance506.6739831
2021-11-24T15:35:25.852176image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
413273.0%
 
423162.9%
 
433122.9%
 
402812.6%
 
392812.6%
 
442712.5%
 
382702.5%
 
452602.4%
 
362342.2%
 
372322.1%
 
Other values (114)809074.4%
 
ValueCountFrequency (%) 
102< 0.1%
 
113< 0.1%
 
1290.1%
 
1370.1%
 
14210.2%
 
ValueCountFrequency (%) 
1391< 0.1%
 
1381< 0.1%
 
1315< 0.1%
 
1302< 0.1%
 
1294< 0.1%
 

Total_Ct_Chng_Q4_Q1
Real number (ℝ≥0)

Distinct count5113
Unique (%)47.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6475065286655576
Minimum0.0
Maximum3.25
Zeros5
Zeros (%)< 0.1%
Memory size85.0 KiB
2021-11-24T15:35:25.912960image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.312098424
Q10.4968741117
median0.6400350781
Q30.778
95-th percentile1
Maximum3.25
Range3.25
Interquartile range (IQR)0.2811258883

Descriptive statistics

Standard deviation0.2302693108
Coefficient of variation (CV)0.3556246935
Kurtosis8.095188764
Mean0.6475065287
Median Absolute Deviation (MAD)0.1400350781
Skewness1.291232781
Sum7040.985993
Variance0.0530239555
2021-11-24T15:35:25.972758image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
11131.0%
 
0.6671111.0%
 
0.51091.0%
 
0.75970.9%
 
0.6760.7%
 
0.714630.6%
 
0.8620.6%
 
0.833550.5%
 
0.778450.4%
 
0.571380.3%
 
Other values (5103)1010592.9%
 
ValueCountFrequency (%) 
05< 0.1%
 
0.0058469749921< 0.1%
 
0.0281< 0.1%
 
0.030286988071< 0.1%
 
0.0381< 0.1%
 
ValueCountFrequency (%) 
3.251< 0.1%
 
32< 0.1%
 
2.8751< 0.1%
 
2.751< 0.1%
 
2.41< 0.1%
 

Avg_Utilization_Ratio
Real number (ℝ≥0)

ZEROS

Distinct count3023
Unique (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22810309851643076
Minimum0.0
Maximum0.999
Zeros3872
Zeros (%)35.6%
Memory size85.0 KiB
2021-11-24T15:35:26.032559image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.09029051318
Q30.416
95-th percentile0.807
Maximum0.999
Range0.999
Interquartile range (IQR)0.416

Descriptive statistics

Standard deviation0.2781451934
Coefficient of variation (CV)1.21938367
Kurtosis-0.2593014475
Mean0.2281030985
Median Absolute Deviation (MAD)0.09029051318
Skewness1.029154209
Sum2480.393093
Variance0.0773647486
2021-11-24T15:35:26.087377image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0387235.6%
 
0.073510.5%
 
0.061210.2%
 
0.048210.2%
 
0.059210.2%
 
0.057190.2%
 
0.045180.2%
 
0.071180.2%
 
0.056180.2%
 
0.07170.2%
 
Other values (3013)679862.5%
 
ValueCountFrequency (%) 
0387235.6%
 
1.120423815e-061< 0.1%
 
4.728281387e-051< 0.1%
 
5.308497479e-051< 0.1%
 
7.841971162e-051< 0.1%
 
ValueCountFrequency (%) 
0.9991< 0.1%
 
0.9951< 0.1%
 
0.99446000861< 0.1%
 
0.99434478591< 0.1%
 
0.9941< 0.1%
 
Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
0
5437
1
5437
ValueCountFrequency (%) 
0543750.0%
 
1543750.0%
 

Interactions

2021-11-24T15:35:07.749786image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:07.890826image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:07.962739image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.031506image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.107333image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.180090image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.254840image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.330093image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.403354image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.478104image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.552368image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.627624image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.699888image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.773641image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.846237image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.918078image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:08.990843image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.061587image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.135343image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.213080image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.288872image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.366625image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.440314image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.518044image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.596686image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.673427image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.749184image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.823935image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:09.970129image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.036017image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.104758image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.169541image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.238236image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.308203image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.376979image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.449352image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.517814image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.590571image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.662958image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.734721image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.805480image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.880230image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:10.949012image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.023750image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.099500image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.169271image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.243027image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.317768image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.393513image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.470259image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.544009image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.621429image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.699169image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.776998image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.851755image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:11.927493image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.003238image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.077091image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.152530image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.224867image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.302607image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.379953image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.548386image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.630117image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.706879image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.787586image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.867322image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:12.947059image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.023805image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.104601image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.181331image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.257076image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.330905image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.405587image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.483481image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.560223image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.637102image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.716828image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.792203image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.874822image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:13.954586image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.036888image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.114563image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.192861image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.270784image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.347035image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.425772image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.500522image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.578262image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.657995image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.737729image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.818458image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.899213image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:14.982934image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.064660image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.148380image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.228113image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.309840image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.389573image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.462330image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.536083image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.606846image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.794306image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.872550image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:15.947804image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.026541image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.100799image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.178539image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.258272image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.336012image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.410761image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.487505image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.562257image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.638001image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.716738image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.792485image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.871222image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:16.951952image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.031685image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.114913image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.193649image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.276372image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.359496image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.442219image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.522949image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.603679image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.683412image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.761656image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.840392image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.915646image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:17.994887image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.074619image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.156346image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.240067image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.319800image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.403520image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.488236image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.571956image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.652686image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.733417image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.813150image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.890439image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:18.968179image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:19.043926image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:19.122662image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
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2021-11-24T15:35:19.286963image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:19.367772image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
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2021-11-24T15:35:20.001469image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
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2021-11-24T15:35:20.154928image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.230703image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.304682image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.380431image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.457372image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.535112image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.616152image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.693093image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.773823image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.854552image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:20.934796image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.013046image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.090791image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.167541image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.243288image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.320031image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.393793image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.470541image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.549280image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.628525image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.709767image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.788010image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.872810image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:21.952529image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.034255image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.113004image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.192708image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.272460image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.347215image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.420974image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.493719image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.570472image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.647211image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.723962image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.803683image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.879470image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:22.959250image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:23.039999image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:23.118814image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:23.197357image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:23.275105image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Correlations

2021-11-24T15:35:26.166330image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-24T15:35:26.319817image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-24T15:35:26.479863image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-11-24T15:35:26.640500image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-11-24T15:35:26.793992image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-11-24T15:35:23.469126image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-11-24T15:35:23.749774image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Sample

First rows

Customer_AgeGenderDependent_countEducation_LevelMarital_StatusIncome_CategoryCard_CategoryMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioAttrition_Flag
035F2GraduateMarriedLess than $40KBlue365245546.018293717.00.6731770461.0000.3300
157F1UneducatedSingleLess than $40KBlue462339129.009129.00.7337733810.8840.0001
259F1GraduateSingleLess than $40KBlue525332636.016191017.00.5654727830.6270.6140
345F4GraduateSingleLess than $40KBlue332133001.02055946.00.8384662700.6280.6850
443M2DoctorateSingle$120K +Blue3453433913.0033913.00.9014160760.9000.0000
563M0CollegeSingle$80K - $120KBlue566229033.009033.00.7804456850.6350.0000
651F3High SchoolMarriedLess than $40KBlue356133025.019121113.00.6744626780.7730.6320
748M3GraduateMarried$80K - $120KBlue3833331501.0031501.00.6983742750.7860.0000
837M2High SchoolMarried$120K +Blue3261134516.0034516.00.9283660591.1070.0000
946M2GraduateDivorced$80K - $120KBlue303332770.012861484.01.0682920740.7210.4640

Last rows

Customer_AgeGenderDependent_countEducation_LevelMarital_StatusIncome_CategoryCard_CategoryMonths_on_bookTotal_Relationship_CountMonths_Inactive_12_monContacts_Count_12_monCredit_LimitTotal_Revolving_BalAvg_Open_To_BuyTotal_Amt_Chng_Q4_Q1Total_Trans_AmtTotal_Trans_CtTotal_Ct_Chng_Q4_Q1Avg_Utilization_RatioAttrition_Flag
1086432F2GraduateMarriedLess than $40KBlue365331438.30000001438.3000000.8378582447400.5820080.0000001
1086552F2UneducatedMarriedLess than $40KBlue376313548.47546325171031.4754630.6930042375410.4699660.7096431
1086661F0CollegeSingleLess than $40KBlue363343808.10711525171291.1071150.5842702335460.7325860.6607211
1086745M2High SchoolSingle$40K - $60KBlue3642115241.13471188314358.0658470.5294612239470.5128110.0577341
1086843M2GraduateMarried$80K - $120KBlue362225004.93022025172487.9302200.5155611634350.3512380.5028721
1086959M1High SchoolSingleLess than $40KBlue501434957.2607415944362.4102050.8394959930680.8856910.1176891
1087055F0DoctorateSingle$40K - $60KBlue455322308.10550302308.1055030.6071052238400.6067590.0000001
1087154M1GraduateMarried$80K - $120KBlue4332311690.52589026511424.6243000.7079862469480.4631020.0223861
1087243F3UneducatedMarriedLess than $40KBlue253223218.32063103218.3206310.4514462099410.4813200.0000001
1087355F3DoctorateSingleLess than $40KBlue474422422.7590933982024.6412750.6309902418510.5489820.1638561